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<div class="title">TensorReductionSycl.h</div>  </div>
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<div class="contents">
<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">// This file is part of Eigen, a lightweight C++ template library</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// for linear algebra.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">// Mehdi Goli    Codeplay Software Ltd.</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment">// Ralph Potter  Codeplay Software Ltd.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment">// Luke Iwanski  Codeplay Software Ltd.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment">// Contact: &lt;eigen@codeplay.com&gt;</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment">// This Source Code Form is subject to the terms of the Mozilla</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment">// Public License v. 2.0. If a copy of the MPL was not distributed</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment">// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160; </div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment">/*****************************************************************</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * TensorReductionSycl.h</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * \brief:</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> *  This is the specialization of the reduction operation. Two phase reduction approach </span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * is used since the GPU does not have Global Synchronization for global memory among </span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * different work-group/thread block. To solve the problem, we need to create two kernels </span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * to reduce the data, where the first kernel reduce the data locally and each local </span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * workgroup/thread-block save the input data into global memory. In the second phase (global reduction)</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * one work-group uses one work-group/thread-block to reduces the intermediate data into one single element. </span></div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> * Here is an NVIDIA presentation explaining the optimized two phase reduction algorithm on GPU:</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="comment"> * https://developer.download.nvidia.com/assets/cuda/files/reduction.pdf</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="comment"> *****************************************************************/</span></div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160; </div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="preprocessor">#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSOR_REDUCTION_SYCL_HPP</span></div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSOR_REDUCTION_SYCL_HPP</span></div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="preprocessor">#include &quot;./InternalHeaderCheck.h&quot;</span></div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160; </div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespaceEigen.html">Eigen</a> {</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="keyword">namespace </span>TensorSycl {</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="keyword">namespace </span>internal {</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160; </div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Op, <span class="keyword">typename</span> CoeffReturnType, <span class="keyword">typename</span> Index, <span class="keywordtype">bool</span> Vectorizable&gt;</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="keyword">struct </span>OpDefiner {</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Vectorise&lt;CoeffReturnType, Eigen::SyclDevice, Vectorizable&gt;::PacketReturnType PacketReturnType;</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;  <span class="keyword">typedef</span> Op type;</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE type get_op(Op &amp;op) { <span class="keywordflow">return</span> op; }</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160; </div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType finalise_op(<span class="keyword">const</span> PacketReturnType &amp;accumulator,</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;                                                                            <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> &amp;) {</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <span class="keywordflow">return</span> accumulator;</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;  }</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;};</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160; </div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> CoeffReturnType, <span class="keyword">typename</span> Index&gt;</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<span class="keyword">struct </span>OpDefiner&lt;<a class="code" href="namespaceEigen.html">Eigen</a>::internal::MeanReducer&lt;CoeffReturnType&gt;, CoeffReturnType, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>, false&gt; {</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;  <span class="keyword">typedef</span> Eigen::internal::SumReducer&lt;CoeffReturnType&gt; type;</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE type get_op(Eigen::internal::MeanReducer&lt;CoeffReturnType&gt; &amp;) {</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;    <span class="keywordflow">return</span> type();</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;  }</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160; </div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType finalise_op(<span class="keyword">const</span> CoeffReturnType &amp;accumulator,</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;                                                                           <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> &amp;scale) {</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    ::Eigen::internal::scalar_quotient_op&lt;CoeffReturnType&gt; quotient_op;</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="keywordflow">return</span> quotient_op(accumulator, CoeffReturnType(scale));</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  }</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;};</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160; </div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> CoeffReturnType, <span class="keyword">typename</span> Index&gt;</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;<span class="keyword">struct </span>OpDefiner&lt;<a class="code" href="namespaceEigen.html">Eigen</a>::internal::MeanReducer&lt;CoeffReturnType&gt;, CoeffReturnType, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>, true&gt; {</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Vectorise&lt;CoeffReturnType, Eigen::SyclDevice, true&gt;::PacketReturnType PacketReturnType;</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  <span class="keyword">typedef</span> Eigen::internal::SumReducer&lt;CoeffReturnType&gt; type;</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE type get_op(Eigen::internal::MeanReducer&lt;CoeffReturnType&gt; &amp;) {</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <span class="keywordflow">return</span> type();</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  }</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160; </div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType finalise_op(<span class="keyword">const</span> PacketReturnType &amp;accumulator,</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;                                                                            <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> &amp;scale) {</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    return ::Eigen::internal::pdiv(accumulator, ::Eigen::internal::pset1&lt;PacketReturnType&gt;(CoeffReturnType(scale)));</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  }</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;};</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160; </div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> CoeffReturnType, <span class="keyword">typename</span> OpType, <span class="keyword">typename</span> InputAccessor, <span class="keyword">typename</span> OutputAccessor, <span class="keyword">typename</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>,</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;          <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> local_range&gt;</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;<span class="keyword">struct </span>SecondStepFullReducer {</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="keyword">typedef</span> cl::sycl::accessor&lt;CoeffReturnType, 1, cl::sycl::access::mode::read_write, cl::sycl::access::target::local&gt;</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;      LocalAccessor;</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;  <span class="keyword">typedef</span> OpDefiner&lt;OpType, CoeffReturnType, Index, true&gt; OpDef;</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> OpDef::type Op;</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;  LocalAccessor scratch;</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  InputAccessor aI;</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  OutputAccessor outAcc;</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  Op op;</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  SecondStepFullReducer(LocalAccessor scratch_, InputAccessor aI_, OutputAccessor outAcc_, OpType op_)</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;      : scratch(scratch_), aI(aI_), outAcc(outAcc_), op(OpDef::get_op(op_)) {}</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160; </div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  <span class="keywordtype">void</span> operator()(cl::sycl::nd_item&lt;1&gt; itemID) {</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <span class="comment">// Our empirical research shows that the best performance will be achieved</span></div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="comment">// when there is only one element per thread to reduce in the second step.</span></div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    <span class="comment">// in this step the second step reduction time is almost negligible.</span></div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    <span class="comment">// Hence, in the second step of reduction the input size is fixed to the</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    <span class="comment">// local size, thus, there is only one element read per thread. The</span></div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    <span class="comment">// algorithm must be changed if the number of reduce per thread in the</span></div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    <span class="comment">// second step is greater than 1. Otherwise, the result will be wrong.</span></div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> localid = itemID.get_local_id(0);</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    <span class="keyword">auto</span> aInPtr = aI.get_pointer() + localid;</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    <span class="keyword">auto</span> aOutPtr = outAcc.get_pointer();</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    CoeffReturnType *scratchptr = scratch.get_pointer();</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    CoeffReturnType accumulator = *aInPtr;</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160; </div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    scratchptr[localid] = op.finalize(accumulator);</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> offset = itemID.get_local_range(0) / 2; offset &gt; 0; offset /= 2) {</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;      itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;      <span class="keywordflow">if</span> (localid &lt; offset) {</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;        op.reduce(scratchptr[localid + offset], &amp;accumulator);</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;        scratchptr[localid] = op.finalize(accumulator);</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;      }</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    }</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <span class="keywordflow">if</span> (localid == 0) *aOutPtr = op.finalize(accumulator);</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;  }</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;};</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160; </div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;<span class="comment">// Full reduction first phase. In this version the vectorization is true and the reduction accept </span></div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;<span class="comment">// any generic reducerOp  e.g( max, min, sum, mean, iamax, iamin, etc ). </span></div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Evaluator, <span class="keyword">typename</span> OpType, <span class="keyword">typename</span> Evaluator::Index local_range&gt;</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;<span class="keyword">class </span>FullReductionKernelFunctor {</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160; <span class="keyword">public</span>:</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Index <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>;</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  <span class="keyword">typedef</span> OpDefiner&lt;OpType, <span class="keyword">typename</span> Evaluator::CoeffReturnType, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>,</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;                    (Evaluator::ReducerTraits::PacketAccess &amp; Evaluator::InputPacketAccess)&gt;</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;      OpDef;</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160; </div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> OpDef::type Op;</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::EvaluatorPointerType EvaluatorPointerType;</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::PacketReturnType PacketReturnType;</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;  <span class="keyword">typedef</span> std::conditional_t&lt;(Evaluator::ReducerTraits::PacketAccess &amp; Evaluator::InputPacketAccess),</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;                                              PacketReturnType, CoeffReturnType&gt; OutType;</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;  <span class="keyword">typedef</span> cl::sycl::accessor&lt;OutType, 1, cl::sycl::access::mode::read_write, cl::sycl::access::target::local&gt;</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;      LocalAccessor;</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;  LocalAccessor scratch;</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;  Evaluator evaluator;</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;  EvaluatorPointerType final_output;</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> rng;</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  Op op;</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160; </div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  FullReductionKernelFunctor(LocalAccessor scratch_, Evaluator evaluator_, EvaluatorPointerType final_output_,</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;                             <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> rng_, OpType op_)</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;      : scratch(scratch_), evaluator(evaluator_), final_output(final_output_), rng(rng_), op(OpDef::get_op(op_)) {}</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160; </div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;  <span class="keywordtype">void</span> operator()(cl::sycl::nd_item&lt;1&gt; itemID) { compute_reduction(itemID); }</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160; </div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> Vect = (Evaluator::ReducerTraits::PacketAccess &amp; Evaluator::InputPacketAccess)&gt;</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::enable_if_t&lt;Vect&gt; compute_reduction(</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;      <span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;itemID) {</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="keyword">auto</span> output_ptr = final_output.get_pointer();</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> VectorizedRange = (rng / Evaluator::PacketSize) * Evaluator::PacketSize;</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalid = itemID.get_global_id(0);</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> localid = itemID.get_local_id(0);</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> step = Evaluator::PacketSize * itemID.get_global_range(0);</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> start = Evaluator::PacketSize * globalid;</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    <span class="comment">// vectorizable parts</span></div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    PacketReturnType packetAccumulator = op.template initializePacket&lt;PacketReturnType&gt;();</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i = start; i &lt; VectorizedRange; i += step) {</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;      op.template reducePacket&lt;PacketReturnType&gt;(evaluator.impl().template packet&lt;Unaligned&gt;(i), &amp;packetAccumulator);</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    }</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;    globalid += VectorizedRange;</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;    <span class="comment">// non vectorizable parts</span></div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i = globalid; i &lt; rng; i += itemID.get_global_range(0)) {</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      op.template reducePacket&lt;PacketReturnType&gt;(</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;          ::Eigen::TensorSycl::internal::PacketWrapper&lt;PacketReturnType, Evaluator::PacketSize&gt;::convert_to_packet_type(</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;              evaluator.impl().coeff(i), op.initialize()),</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;          &amp;packetAccumulator);</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    }</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    scratch[localid] = packetAccumulator =</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;        OpDef::finalise_op(op.template finalizePacket&lt;PacketReturnType&gt;(packetAccumulator), rng);</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    <span class="comment">// reduction parts // Local size is always power of 2</span></div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> offset = local_range / 2; offset &gt; 0; offset /= 2) {</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;      itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;      <span class="keywordflow">if</span> (localid &lt; offset) {</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;        op.template reducePacket&lt;PacketReturnType&gt;(scratch[localid + offset], &amp;packetAccumulator);</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        scratch[localid] = op.template finalizePacket&lt;PacketReturnType&gt;(packetAccumulator);</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;      }</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    }</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    <span class="keywordflow">if</span> (localid == 0) {</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;      output_ptr[itemID.get_group(0)] =</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;          op.finalizeBoth(op.initialize(), op.template finalizePacket&lt;PacketReturnType&gt;(packetAccumulator));</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    }</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;  }</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160; </div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> Vect = (Evaluator::ReducerTraits::PacketAccess &amp; Evaluator::InputPacketAccess)&gt;</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::enable_if_t&lt;!Vect&gt; compute_reduction(</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;      <span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;itemID) {</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;    <span class="keyword">auto</span> output_ptr = final_output.get_pointer();</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalid = itemID.get_global_id(0);</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> localid = itemID.get_local_id(0);</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;    <span class="comment">// vectorizable parts</span></div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;    CoeffReturnType accumulator = op.initialize();</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    <span class="comment">// non vectorizable parts</span></div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i = globalid; i &lt; rng; i += itemID.get_global_range(0)) {</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;      op.reduce(evaluator.impl().coeff(i), &amp;accumulator);</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    }</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;    scratch[localid] = accumulator = OpDef::finalise_op(op.finalize(accumulator), rng);</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160; </div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    <span class="comment">// reduction parts. the local size is always power of 2</span></div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> offset = local_range / 2; offset &gt; 0; offset /= 2) {</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;      itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;      <span class="keywordflow">if</span> (localid &lt; offset) {</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        op.reduce(scratch[localid + offset], &amp;accumulator);</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        scratch[localid] = op.finalize(accumulator);</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;      }</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    }</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    <span class="keywordflow">if</span> (localid == 0) {</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;      output_ptr[itemID.get_group(0)] = op.finalize(accumulator);</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    }</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;  }</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;};</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160; </div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Evaluator, <span class="keyword">typename</span> OpType&gt;</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;<span class="keyword">class </span>GenericNondeterministicReducer {</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160; <span class="keyword">public</span>:</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::EvaluatorPointerType EvaluatorPointerType;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Index <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>;</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;  <span class="keyword">typedef</span> OpDefiner&lt;OpType, CoeffReturnType, Index, false&gt; OpDef;</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> OpDef::type Op;</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;  <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scratch&gt;</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  GenericNondeterministicReducer(Scratch, Evaluator evaluator_, EvaluatorPointerType output_accessor_, OpType functor_,</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;                       <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> range_, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_values_to_reduce_)</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;      : evaluator(evaluator_),</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;        output_accessor(output_accessor_),</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;        functor(OpDef::get_op(functor_)),</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;        range(range_),</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;        num_values_to_reduce(num_values_to_reduce_) {}</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160; </div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;  <span class="keywordtype">void</span> operator()(cl::sycl::nd_item&lt;1&gt; itemID) {</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    <span class="keyword">auto</span> output_accessor_ptr = output_accessor.get_pointer();</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalid = <span class="keyword">static_cast&lt;</span><a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a><span class="keyword">&gt;</span>(itemID.get_global_linear_id());</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    <span class="keywordflow">if</span> (globalid &lt; range) {</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;      CoeffReturnType accum = functor.initialize();</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;      Eigen::internal::GenericDimReducer&lt;Evaluator::NumReducedDims - 1, Evaluator, Op&gt;::reduce(</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;          evaluator, evaluator.firstInput(globalid), functor, &amp;accum);</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;      output_accessor_ptr[globalid] = OpDef::finalise_op(functor.finalize(accum), num_values_to_reduce);</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;    }</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;  }</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160; </div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160; <span class="keyword">private</span>:</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;  Evaluator evaluator;</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;  EvaluatorPointerType output_accessor;</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;  Op functor;</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;  <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> range;</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;  <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_values_to_reduce;</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;};</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160; </div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;<span class="keyword">enum class</span> reduction_dim { inner_most, outer_most };</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;<span class="comment">// default is preserver</span></div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Evaluator, <span class="keyword">typename</span> OpType, <span class="keyword">typename</span> PannelParameters, reduction_dim rt&gt;</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;<span class="keyword">struct </span>PartialReductionKernel {</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::EvaluatorPointerType EvaluatorPointerType;</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Index <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>;</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;  <span class="keyword">typedef</span> OpDefiner&lt;OpType, CoeffReturnType, Index, false&gt; OpDef;</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> OpDef::type Op;</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;  <span class="keyword">typedef</span> cl::sycl::accessor&lt;CoeffReturnType, 1, cl::sycl::access::mode::read_write, cl::sycl::access::target::local&gt;</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;      ScratchAcc;</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;  ScratchAcc scratch;</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;  Evaluator evaluator;</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;  EvaluatorPointerType output_accessor;</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;  Op op;</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;  <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> preserve_elements_num_groups;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;  <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> reduce_elements_num_groups;</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;  <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_preserve;</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;  <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_reduce;</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160; </div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;  PartialReductionKernel(ScratchAcc scratch_, Evaluator evaluator_, EvaluatorPointerType output_accessor_, OpType op_,</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;                         <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> preserve_elements_num_groups_, <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> reduce_elements_num_groups_,</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;                         <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_preserve_, <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_reduce_)</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;      : scratch(scratch_),</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        evaluator(evaluator_),</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;        output_accessor(output_accessor_),</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;        op(OpDef::get_op(op_)),</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;        preserve_elements_num_groups(preserve_elements_num_groups_),</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;        reduce_elements_num_groups(reduce_elements_num_groups_),</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;        num_coeffs_to_preserve(num_coeffs_to_preserve_),</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;        num_coeffs_to_reduce(num_coeffs_to_reduce_) {}</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160; </div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> element_wise_reduce(<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalRId, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalPId,</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;                                                                 CoeffReturnType &amp;accumulator) {</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    <span class="keywordflow">if</span> (globalPId &gt;= num_coeffs_to_preserve) {</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;      <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;    }</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> global_offset = rt == reduction_dim::outer_most ? globalPId + (globalRId * num_coeffs_to_preserve)</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;                                                          : globalRId + (globalPId * num_coeffs_to_reduce);</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> localOffset = globalRId;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160; </div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> per_thread_local_stride = PannelParameters::LocalThreadSizeR * reduce_elements_num_groups;</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> per_thread_global_stride =</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;        rt == reduction_dim::outer_most ? num_coeffs_to_preserve * per_thread_local_stride : per_thread_local_stride;</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i = globalRId; i &lt; num_coeffs_to_reduce; i += per_thread_local_stride) {</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;      op.reduce(evaluator.impl().coeff(global_offset), &amp;accumulator);</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;      localOffset += per_thread_local_stride;</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;      global_offset += per_thread_global_stride;</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;    }</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;  }</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> operator()(cl::sycl::nd_item&lt;1&gt; itemID) {</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> linearLocalThreadId = itemID.get_local_id(0);</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> pLocalThreadId = rt == reduction_dim::outer_most ? linearLocalThreadId % PannelParameters::LocalThreadSizeP</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;                                                           : linearLocalThreadId / PannelParameters::LocalThreadSizeR;</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> rLocalThreadId = rt == reduction_dim::outer_most ? linearLocalThreadId / PannelParameters::LocalThreadSizeP</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;                                                           : linearLocalThreadId % PannelParameters::LocalThreadSizeR;</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> pGroupId = rt == reduction_dim::outer_most ? itemID.get_group(0) % preserve_elements_num_groups</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;                                                           : itemID.get_group(0) / reduce_elements_num_groups;</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> rGroupId = rt == reduction_dim::outer_most ? itemID.get_group(0) / preserve_elements_num_groups</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;                                                           : itemID.get_group(0) % reduce_elements_num_groups;</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160; </div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalPId = pGroupId * PannelParameters::LocalThreadSizeP + pLocalThreadId;</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalRId = rGroupId * PannelParameters::LocalThreadSizeR + rLocalThreadId;</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;    <span class="keyword">auto</span> scratchPtr = scratch.get_pointer().get();</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;    <span class="keyword">auto</span> outPtr =</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;        output_accessor.get_pointer() + (reduce_elements_num_groups &gt; 1 ? rGroupId * num_coeffs_to_preserve : 0);</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;    CoeffReturnType accumulator = op.initialize();</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160; </div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    element_wise_reduce(globalRId, globalPId, accumulator);</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160; </div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;    accumulator = OpDef::finalise_op(op.finalize(accumulator), num_coeffs_to_reduce);</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;    scratchPtr[pLocalThreadId + rLocalThreadId * (PannelParameters::LocalThreadSizeP + PannelParameters::BC)] =</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;        accumulator;</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;    <span class="keywordflow">if</span> (rt == reduction_dim::inner_most) {</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;      pLocalThreadId = linearLocalThreadId % PannelParameters::LocalThreadSizeP;</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;      rLocalThreadId = linearLocalThreadId / PannelParameters::LocalThreadSizeP;</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;      globalPId = pGroupId * PannelParameters::LocalThreadSizeP + pLocalThreadId;</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;    }</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160; </div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    <span class="comment">/* Apply the reduction operation between the current local</span></div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;<span class="comment">     * id and the one on the other half of the vector. */</span></div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;    <span class="keyword">auto</span> out_scratch_ptr =</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;        scratchPtr + (pLocalThreadId + (rLocalThreadId * (PannelParameters::LocalThreadSizeP + PannelParameters::BC)));</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;    itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    <span class="keywordflow">if</span> (rt == reduction_dim::inner_most) {</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;      accumulator = *out_scratch_ptr;</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;    }</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;    <span class="comment">// The Local LocalThreadSizeR is always power of 2</span></div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> offset = PannelParameters::LocalThreadSizeR &gt;&gt; 1; offset &gt; 0; offset &gt;&gt;= 1) {</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;      <span class="keywordflow">if</span> (rLocalThreadId &lt; offset) {</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;        op.reduce(out_scratch_ptr[(PannelParameters::LocalThreadSizeP + PannelParameters::BC) * offset], &amp;accumulator);</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;        <span class="comment">// The result has already been divided for mean reducer in the</span></div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;        <span class="comment">// previous reduction so no need to divide furthermore</span></div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;        *out_scratch_ptr = op.finalize(accumulator);</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;      }</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;      <span class="comment">/* All threads collectively read from global memory into local.</span></div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;<span class="comment">       * The barrier ensures all threads&#39; IO is resolved before</span></div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;<span class="comment">       * execution continues (strictly speaking, all threads within</span></div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;<span class="comment">       * a single work-group - there is no co-ordination between</span></div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;<span class="comment">       * work-groups, only work-items). */</span></div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;      itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    }</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160; </div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;    <span class="keywordflow">if</span> (rLocalThreadId == 0 &amp;&amp; (globalPId &lt; num_coeffs_to_preserve)) {</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;      outPtr[globalPId] = op.finalize(accumulator);</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;    }</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;  }</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;};</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160; </div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> OutScalar, <span class="keyword">typename</span> Index, <span class="keyword">typename</span> InputAccessor, <span class="keyword">typename</span> OutputAccessor, <span class="keyword">typename</span> OpType&gt;</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;<span class="keyword">struct </span>SecondStepPartialReduction {</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;  <span class="keyword">typedef</span> OpDefiner&lt;OpType, OutScalar, Index, false&gt; OpDef;</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> OpDef::type Op;</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;  <span class="keyword">typedef</span> cl::sycl::accessor&lt;OutScalar, 1, cl::sycl::access::mode::read_write, cl::sycl::access::target::local&gt;</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;      ScratchAccessor;</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;  InputAccessor input_accessor;</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;  OutputAccessor output_accessor;</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;  Op op;</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;  <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_preserve;</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;  <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_reduce;</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160; </div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE SecondStepPartialReduction(ScratchAccessor, InputAccessor input_accessor_,</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;                                                                   OutputAccessor output_accessor_, OpType op_,</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;                                                                   <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_preserve_,</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;                                                                   <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_reduce_)</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;      : input_accessor(input_accessor_),</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;        output_accessor(output_accessor_),</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;        op(OpDef::get_op(op_)),</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;        num_coeffs_to_preserve(num_coeffs_to_preserve_),</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;        num_coeffs_to_reduce(num_coeffs_to_reduce_) {}</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160; </div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> operator()(cl::sycl::nd_item&lt;1&gt; itemID) {</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalId = itemID.get_global_id(0);</div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160; </div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;    <span class="keywordflow">if</span> (globalId &gt;= num_coeffs_to_preserve) <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160; </div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;    <span class="keyword">auto</span> in_ptr = input_accessor.get_pointer() + globalId;</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160; </div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;    OutScalar accumulator = op.initialize();</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;<span class="comment">// num_coeffs_to_reduce is not bigger that 256</span></div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;    <span class="keywordflow">for</span> (<a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i = 0; i &lt; num_coeffs_to_reduce; i++) {</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;      op.reduce(*in_ptr, &amp;accumulator);</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;      in_ptr += num_coeffs_to_preserve;</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;    }</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;    output_accessor.get_pointer()[globalId] = op.finalize(accumulator);</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;  }</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;};  <span class="comment">// namespace internal</span></div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160; </div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Index, Index LTP, Index LTR, <span class="keywordtype">bool</span> BC_&gt;</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;<span class="keyword">struct </span>ReductionPannel {</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> LocalThreadSizeP = LTP;</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> LocalThreadSizeR = LTR;</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> BC = BC_;</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;};</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160; </div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Self, <span class="keyword">typename</span> Op, TensorSycl::<span class="keywordtype">int</span>ernal::reduction_dim rt&gt;</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;<span class="keyword">struct </span>PartialReducerLauncher {</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Self::EvaluatorPointerType EvaluatorPointerType;</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Self::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Self::Storage Storage;</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Self::Index <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>;</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;  <span class="keyword">typedef</span> ReductionPannel&lt;typename Self::Index, EIGEN_SYCL_LOCAL_THREAD_DIM0, EIGEN_SYCL_LOCAL_THREAD_DIM1, true&gt;</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;      PannelParameters;</div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160; </div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;  <span class="keyword">typedef</span> PartialReductionKernel&lt;Self, Op, PannelParameters, rt&gt; SyclReducerKerneType;</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160; </div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">bool</span> run(<span class="keyword">const</span> Self &amp;<span class="keyword">self</span>, <span class="keyword">const</span> Op &amp;reducer, <span class="keyword">const</span> Eigen::SyclDevice &amp;dev, EvaluatorPointerType output,</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;                  <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_reduce, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_coeffs_to_preserve) {</div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> roundUpP = roundUp(num_coeffs_to_preserve, PannelParameters::LocalThreadSizeP);</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160; </div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;    <span class="comment">// getPowerOfTwo makes sure local range is power of 2 and &lt;=</span></div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;    <span class="comment">// maxSyclThreadPerBlock this will help us to avoid extra check on the</span></div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;    <span class="comment">// kernel</span></div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;    static_assert(!((PannelParameters::LocalThreadSizeP * PannelParameters::LocalThreadSizeR) &amp;</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;                    (PannelParameters::LocalThreadSizeP * PannelParameters::LocalThreadSizeR - 1)),</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;                  <span class="stringliteral">&quot;The Local thread size must be a power of 2 for the reduction &quot;</span></div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;                  <span class="stringliteral">&quot;operation&quot;</span>);</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160; </div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;    EIGEN_CONSTEXPR <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> localRange = PannelParameters::LocalThreadSizeP * PannelParameters::LocalThreadSizeR;</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;    <span class="comment">// In this step, we force the code not to be more than 2-step reduction:</span></div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;    <span class="comment">// Our empirical research shows that if each thread reduces at least 64</span></div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;    <span class="comment">// elemnts individually, we get better performance. However, this can change</span></div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;    <span class="comment">// on different platforms. In this step we force the code not to be</span></div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;    <span class="comment">// morthan step reduction: Our empirical research shows that for inner_most</span></div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;    <span class="comment">// dim reducer, it is better to have 8 group in a reduce dimension for sizes</span></div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;    <span class="comment">// &gt; 1024 to achieve the best performance.</span></div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> reductionPerThread = 64;</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> cu = dev.getPowerOfTwo(dev.getNumSyclMultiProcessors(), <span class="keyword">true</span>);</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> pNumGroups = roundUpP / PannelParameters::LocalThreadSizeP;</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> rGroups = (cu + pNumGroups - 1) / pNumGroups;</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> rNumGroups = num_coeffs_to_reduce &gt; reductionPerThread * localRange ? std::min(rGroups, localRange) : 1;</div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> globalRange = pNumGroups * rNumGroups * localRange;</div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160; </div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;    EIGEN_CONSTEXPR <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> scratchSize =</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;        PannelParameters::LocalThreadSizeR * (PannelParameters::LocalThreadSizeP + PannelParameters::BC);</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;    <span class="keyword">auto</span> thread_range = cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(globalRange), cl::sycl::range&lt;1&gt;(localRange));</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;    <span class="keywordflow">if</span> (rNumGroups &gt; 1) {</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;      CoeffReturnType *temp_pointer = <span class="keyword">static_cast&lt;</span>CoeffReturnType *<span class="keyword">&gt;</span>(</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;          dev.allocate_temp(num_coeffs_to_preserve * rNumGroups * <span class="keyword">sizeof</span>(CoeffReturnType)));</div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;      EvaluatorPointerType temp_accessor = dev.get(temp_pointer);</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;      dev.template unary_kernel_launcher&lt;CoeffReturnType, SyclReducerKerneType&gt;(</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;          <span class="keyword">self</span>, temp_accessor, thread_range, scratchSize, reducer, pNumGroups, rNumGroups, num_coeffs_to_preserve,</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;          num_coeffs_to_reduce);</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160; </div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;      <span class="keyword">typedef</span> SecondStepPartialReduction&lt;CoeffReturnType, Index, EvaluatorPointerType, EvaluatorPointerType, Op&gt;</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;          SecondStepPartialReductionKernel;</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160; </div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;      dev.template unary_kernel_launcher&lt;CoeffReturnType, SecondStepPartialReductionKernel&gt;(</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;          temp_accessor, output,</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;          cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(pNumGroups * localRange), cl::sycl::range&lt;1&gt;(localRange)), <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>(1),</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;          reducer, num_coeffs_to_preserve, rNumGroups);</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160; </div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;      <span class="keyword">self</span>.device().deallocate_temp(temp_pointer);</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;      dev.template unary_kernel_launcher&lt;CoeffReturnType, SyclReducerKerneType&gt;(</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;          <span class="keyword">self</span>, output, thread_range, scratchSize, reducer, pNumGroups, rNumGroups, num_coeffs_to_preserve,</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;          num_coeffs_to_reduce);</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;    }</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;  }</div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;};</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;}  <span class="comment">// namespace internal</span></div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;}  <span class="comment">// namespace TensorSycl</span></div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160; </div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;<span class="keyword">namespace </span>internal {</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160; </div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Self, <span class="keyword">typename</span> Op, <span class="keywordtype">bool</span> Vectorizable&gt;</div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;<span class="keyword">struct </span>FullReducer&lt;Self, Op, <a class="code" href="namespaceEigen.html">Eigen</a>::SyclDevice, Vectorizable&gt; {</div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Self::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Self::EvaluatorPointerType EvaluatorPointerType;</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> HasOptimizedImplementation = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">int</span> PacketSize = Self::PacketAccess ? Self::PacketSize : 1;</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">void</span> run(<span class="keyword">const</span> Self &amp;<span class="keyword">self</span>, Op &amp;reducer, <span class="keyword">const</span> Eigen::SyclDevice &amp;dev, EvaluatorPointerType data) {</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;    <span class="keyword">typedef</span> std::conditional_t&lt;Self::PacketAccess, typename Self::PacketReturnType, CoeffReturnType&gt; OutType;</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;    static_assert(!((EIGEN_SYCL_LOCAL_THREAD_DIM0 * EIGEN_SYCL_LOCAL_THREAD_DIM1) &amp;</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;                    (EIGEN_SYCL_LOCAL_THREAD_DIM0 * EIGEN_SYCL_LOCAL_THREAD_DIM1 - 1)),</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;                  <span class="stringliteral">&quot;The Local thread size must be a power of 2 for the reduction &quot;</span></div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;                  <span class="stringliteral">&quot;operation&quot;</span>);</div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;    EIGEN_CONSTEXPR <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> local_range = EIGEN_SYCL_LOCAL_THREAD_DIM0 * EIGEN_SYCL_LOCAL_THREAD_DIM1;</div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160; </div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;    <span class="keyword">typename</span> Self::Index inputSize = <span class="keyword">self</span>.impl().dimensions().TotalSize();</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;    <span class="comment">// In this step we force the code not to be more than 2-step reduction:</span></div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;    <span class="comment">// Our empirical research shows that if each thread reduces at least 512</span></div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;    <span class="comment">// elemnts individually, we get better performance.</span></div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> reductionPerThread = 2048;</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;    <span class="comment">// const Index num_work_group =</span></div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;    <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> reductionGroup = dev.getPowerOfTwo(</div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;        (inputSize + (reductionPerThread * local_range - 1)) / (reductionPerThread * local_range), <span class="keyword">true</span>);</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> num_work_group = std::min(reductionGroup, local_range);</div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;    <span class="comment">// 1</span></div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;    <span class="comment">// ? local_range</span></div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;    <span class="comment">// : 1);</span></div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;    <span class="keyword">const</span> <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> global_range = num_work_group * local_range;</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160; </div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;    <span class="keyword">auto</span> thread_range = cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(global_range), cl::sycl::range&lt;1&gt;(local_range));</div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;    <span class="keyword">typedef</span> TensorSycl::internal::FullReductionKernelFunctor&lt;Self, Op, local_range&gt; reduction_kernel_t;</div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;    <span class="keywordflow">if</span> (num_work_group &gt; 1) {</div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;      CoeffReturnType *temp_pointer =</div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;          <span class="keyword">static_cast&lt;</span>CoeffReturnType *<span class="keyword">&gt;</span>(dev.allocate_temp(num_work_group * <span class="keyword">sizeof</span>(CoeffReturnType)));</div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;      <span class="keyword">typename</span> Self::EvaluatorPointerType tmp_global_accessor = dev.get(temp_pointer);</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;      dev.template unary_kernel_launcher&lt;OutType, reduction_kernel_t&gt;(<span class="keyword">self</span>, tmp_global_accessor, thread_range,</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;                                                                      local_range, inputSize, reducer);</div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160; </div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;      <span class="keyword">typedef</span> TensorSycl::internal::SecondStepFullReducer&lt;CoeffReturnType, Op, EvaluatorPointerType,</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;                                                          EvaluatorPointerType, <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>, local_range&gt;</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;          GenericRKernel;</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;      dev.template unary_kernel_launcher&lt;CoeffReturnType, GenericRKernel&gt;(</div>
<div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;          tmp_global_accessor, data,</div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;          cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(num_work_group), cl::sycl::range&lt;1&gt;(num_work_group)), num_work_group,</div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;          reducer);</div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160; </div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;      dev.deallocate_temp(temp_pointer);</div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;      dev.template unary_kernel_launcher&lt;OutType, reduction_kernel_t&gt;(<span class="keyword">self</span>, data, thread_range, local_range, inputSize,</div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;                                                                      reducer);</div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;    }</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;  }</div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;};</div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;<span class="comment">// vectorizable inner_most most dim preserver</span></div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;<span class="comment">// col reduction</span></div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Self, <span class="keyword">typename</span> Op&gt;</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;<span class="keyword">struct </span>OuterReducer&lt;Self, Op, <a class="code" href="namespaceEigen.html">Eigen</a>::SyclDevice&gt; {</div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> HasOptimizedImplementation = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160; </div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">bool</span> run(<span class="keyword">const</span> Self &amp;<span class="keyword">self</span>, <span class="keyword">const</span> Op &amp;reducer, <span class="keyword">const</span> Eigen::SyclDevice &amp;dev,</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;                  <span class="keyword">typename</span> Self::EvaluatorPointerType output, <span class="keyword">typename</span> Self::Index num_coeffs_to_reduce,</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;                  <span class="keyword">typename</span> Self::Index num_coeffs_to_preserve) {</div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;    return ::Eigen::TensorSycl::internal::PartialReducerLauncher&lt;</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;        Self, Op, ::Eigen::TensorSycl::internal::reduction_dim::outer_most&gt;::run(<span class="keyword">self</span>, reducer, dev, output,</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;                                                                                 num_coeffs_to_reduce,</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;                                                                                 num_coeffs_to_preserve);</div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;  }</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;};</div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;<span class="comment">// row reduction</span></div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Self, <span class="keyword">typename</span> Op&gt;</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;<span class="keyword">struct </span>InnerReducer&lt;Self, Op, <a class="code" href="namespaceEigen.html">Eigen</a>::SyclDevice&gt; {</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> HasOptimizedImplementation = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160; </div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">bool</span> run(<span class="keyword">const</span> Self &amp;<span class="keyword">self</span>, <span class="keyword">const</span> Op &amp;reducer, <span class="keyword">const</span> Eigen::SyclDevice &amp;dev,</div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;                  <span class="keyword">typename</span> Self::EvaluatorPointerType output, <span class="keyword">typename</span> Self::Index num_coeffs_to_reduce,</div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;                  <span class="keyword">typename</span> Self::Index num_coeffs_to_preserve) {</div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;    return ::Eigen::TensorSycl::internal::PartialReducerLauncher&lt;</div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;        Self, Op, ::Eigen::TensorSycl::internal::reduction_dim::inner_most&gt;::run(<span class="keyword">self</span>, reducer, dev, output,</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;                                                                                 num_coeffs_to_reduce,</div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;                                                                                 num_coeffs_to_preserve);</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;  }</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;};</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160; </div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;<span class="comment">// ArmgMax uses this kernel for partial reduction//</span></div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;<span class="comment">// TODO(@mehdi.goli) come up with a better kernel</span></div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;<span class="comment">// generic partial reduction</span></div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Self, <span class="keyword">typename</span> Op&gt;</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;<span class="keyword">struct </span>GenericReducer&lt;Self, Op, <a class="code" href="namespaceEigen.html">Eigen</a>::SyclDevice&gt; {</div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> HasOptimizedImplementation = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">bool</span> run(<span class="keyword">const</span> Self &amp;<span class="keyword">self</span>, <span class="keyword">const</span> Op &amp;reducer, <span class="keyword">const</span> Eigen::SyclDevice &amp;dev,</div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;                  <span class="keyword">typename</span> Self::EvaluatorPointerType output, <span class="keyword">typename</span> Self::Index num_values_to_reduce,</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;                  <span class="keyword">typename</span> Self::Index num_coeffs_to_preserve) {</div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;    <span class="keyword">typename</span> Self::Index range, GRange, tileSize;</div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;    dev.parallel_for_setup(num_coeffs_to_preserve, tileSize, range, GRange);</div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160; </div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;    dev.template unary_kernel_launcher&lt;<span class="keyword">typename</span> Self::CoeffReturnType,</div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;                                       TensorSycl::internal::GenericNondeterministicReducer&lt;Self, Op&gt;&gt;(</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;        <span class="keyword">self</span>, output, cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(GRange), cl::sycl::range&lt;1&gt;(tileSize)), <a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>(1),</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;        reducer, range, (num_values_to_reduce != 0) ? num_values_to_reduce : <span class="keyword">static_cast&lt;</span><a class="codeRef" href="../namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a><span class="keyword">&gt;</span>(1));</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;  }</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;};</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160; </div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;}  <span class="comment">// namespace internal</span></div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;}  <span class="comment">// namespace Eigen</span></div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160; </div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;<span class="preprocessor">#endif  </span><span class="comment">// UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSOR_REDUCTION_SYCL_HPP</span></div>
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